INVESTIGADORES
MONGE Maria Eugenia
congresos y reuniones científicas
Título:
Prostate Cancer-induced Changes in the Human Blood Serum Metabolome
Autor/es:
CHRISTINA M. JONES; TRAN Q. LONG; XIAOLING ZANG; MARÍA E. MONGE; MANSHUI ZHOU; L. DEETTE WALKER; ALEXANDER GRAY; JOHN F. MCDONALD; FACUNDO M. FERNÁNDEZ
Lugar:
Atlanta
Reunión:
Conferencia; Georgia Tech Research and Innovation Conference; 2013
Resumen:
Prostate cancer is the sixth deadliest cancer among men. Although the Prostate-Specific Antigen (PSA) test has been widely used to screen for prostate cancer, certain advisory groups recommend against its use because the potential benefits do not outweigh the expected harms. That is, it suffers from several problems including over-diagnosis, false positive results and over-treatment. These drawbacks lead to the increased interest of discovering new differential biochemical modifications which could improve the specificity of prostate cancer diagnosis. Current research has shown that several metabolic alterations are associated with prostate cancer, and sarcosine has been suggested as a biomarker for the aggressive form of this disease. However, global metabolome modifications induced by prostate cancer are still not well understood, and more robust models are being developed for improved understanding of the disease progression and more reliable prostate cancer detection. In this study, untargeted metabolomic profiling of age-matched serum samples from prostate cancer patients and healthy individuals was performed using Ultra Performance Liquid Chromatography coupled to mass spectrometry (UPLC-MS). High resolution mass spectra were acquired in negative ionization mode with a Q-TOF mass analyzer across the 50-1200 m/z range. Metabolomic features were extracted from all chromatograms and analyzed using support vector machines. Samples were successfully classified as cancerous or healthy based on the metabolomic features with 92% accuracy. Our current work includes identification of the metabolomic features responsible for class discrimination, providing further insights into the biological pathways associated with the disease.